ArticlePLoS biology2020
Superspreading events in the transmission dynamics of SARS-CoV-2: Opportunities for interventions and control.
Article in PLoS biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
169 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Workplace interventions to reduce the risk of SARS-CoV-2 infection outside of healthcare settings.The Cochrane database of systematic reviews · 2024Pooled it
- Superspreading, overdispersion and their implications in the SARS-CoV-2 (COVID-19) pandemic: a systematic review and meta-analysis of the literature.BMC public health · 2023Pooled it
- Workplace interventions to reduce the risk of SARS-CoV-2 infection outside of healthcare settings.The Cochrane database of systematic reviews · 2022Pooled it
- Non-pharmacological measures implemented in the setting of long-term care facilities to prevent SARS-CoV-2 infections and their consequences: a rapid review.The Cochrane database of systematic reviews · 2021Pooled it
- The role of asymptomatic and pre-symptomatic infection in SARS-CoV-2 transmission-a living systematic review.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2021Pooled it
- Same-day SARS-CoV-2 antigen test screening in an indoor mass-gathering live music event: a randomised controlled trial.The Lancet. Infectious diseases · 2021Trial
- Coupled epidemiological and wastewater modeling at the urban scale: A case study for Munich.iScience · 2026Article
- Tracking the shifting landscape of SARS-CoV-2 variants in Lebanon among healthcare workers and hospitalized patients.Microbiology spectrum · 2026Article
- Mechanics of pandemics.EClinicalMedicine · 2026Review
- Tracking Dynamics of Superspreading Through Contacts, Exposures, and Transmissions in Edge-Based Network Epidemics.Bulletin of mathematical biology · 2026Article
- Quantifying the role of pre-existing tissue resident cellular immunity in limiting respiratory virus transmission.PLoS pathogens · 2026Article
- Sensitivity analysis of epidemic forecasting and spreading on networks with probability generating functions.Journal of the Royal Society, Interface · 2026Article
- Mobility-driven synthetic contact matrices as a scalable solution for real-time pandemic response modeling.Nature communications · 2026Article
- Chronic infections can generate SARS-CoV-2-like bursts of viral evolution without epistasis.Virus evolution · 2026Article
- Complex multiannual cycles ofProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Social, mobility and contact networks in shaping health behaviours and infectious disease dynamics: a scoping review.Infectious diseases of poverty · 2025Article
- Identifying Social-Epidemiological Roles Associated with Viral Exposure Using Regular Equivalence Blockmodeling.medRxiv : the preprint server for health sciences · 2025Article
- Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Review
- The Kinship Formula: Inferring the numbers of all kin from any structured population projection model.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
109 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19) disease, has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used-appropriately and less appropriately-to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, often dominated by a small number of individuals, and heavily influenced by superspreading events (SSEs). The distinct transmission features of SARS-CoV-2, e.g., high stochasticity under low prevalence (as compared to other pathogens, such as influenza), and the central role played by SSEs on transmission dynamics cannot be overlooked. Many explosive SSEs have occurred in indoor settings, stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, produce processing facilities, fish factories, cruise ships, family gatherings, parties, and nightclubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity to effectively contain outbreaks with targeted interventions to eliminate SSEs. Here, we describe the different types of SSEs, how they influence transmission, empirical evidence for their role in the COVID-19 pandemic, and give recommendations for control of SARS-CoV-2.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.